Fast Fashion vs. Thrifted Clothing LCA Comparison

ISEF Category: Earth and Environmental Sciences

Subcategory: Other  ·  Difficulty: Intermediate  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

A cheap T-shirt can hide a bigger carbon footprint than you think. The real impact depends on how the fiber was made, shipped, washed, and worn. That makes clothing a great topic for a science fair project, because you can turn a shopping habit into a data problem. You can also build a tool that helps teens make smarter choices without guessing.

What Is It?

This project compares the carbon footprint of fast fashion and thrifted clothing by using life-cycle assessment, or LCA. LCA means you track emissions across a product’s full life, from raw materials to disposal. Think of it like tracing every step in a relay race, not just the finish line. A shirt does not start its footprint when it lands in a store. Cotton farming, polyester production, dyeing, transport, washing, drying, and resale all add up.

Thrifted clothing often seems greener because the item already exists, but the answer is not always simple. A secondhand shirt can still carry past impacts from its first life, and shipping, cleaning, and extra packaging can add some emissions too. Your project asks whether buying used actually lowers carbon impact by enough to matter, and under what assumptions. That gives you a clear way to test a real-world claim with public data instead of opinions.

Why This Is a Good Topic

This is a strong science fair topic because you can study a real consumer choice with public data, clear assumptions, and math you can explain. You do not need a wet lab. You need careful sources, good organization, and honest uncertainty analysis. The project connects to climate change, waste, and teen buying habits, so your audience will care about the result. You can also learn how to compare products using data instead of marketing claims.

Research Questions

• How does the estimated carbon footprint of a new fast-fashion shirt compare with a thrifted shirt over one wear cycle?
• What is the effect of fabric type, such as cotton, polyester, or a blend, on the life-cycle carbon footprint of clothing?
• Does the number of wears before disposal change which option has the lower carbon footprint?
• To what extent does laundry method, such as machine drying versus air drying, change the total footprint of a garment?
• Which assumptions in a clothing LCA create the largest uncertainty in the final carbon estimate?
• How does shipping distance affect the comparison between newly bought clothing and thrifted clothing?
• What is the effect of reusing the same garment for multiple seasons on the carbon footprint per wear?

Basic Materials

• Laptop or desktop computer with internet access.
• Spreadsheet software such as Google Sheets or Excel.
• Public LCA inventory sources and reports for textiles.
• Scientific calculator.
• Notebook or digital notes for tracking assumptions.
• Image files or screenshots for documenting source data.
• Basic graphing tool for charts and uncertainty plots.
• Access to a printer or PDF reader for reading articles and reports.

Advanced Materials

• Computer with Python installed.
• Jupyter Notebook.
• Public LCA databases and reports for textile production.
• Monte Carlo simulation package in Python.
• Version control tool such as Git, if available.
• GIS or transport-distance data, if you want to model shipping routes.
• ImageJ, if you plan to extract values from figures in published reports.
• Reference manager such as Zotero for organizing sources.

Software & Tools

• Google Sheets: Organizes input data, runs simple calculations, and makes comparison charts.
• Python: Runs Monte Carlo simulations and sensitivity analysis for footprint estimates.
• Jupyter Notebook: Keeps code, notes, and plots in one place for easy revision.
• Zotero: Stores papers, reports, and citation details in one library.
• ImageJ: Extracts values from graphs or figures in published reports when raw tables are missing.

Experiment Steps

1. Define one clothing item pair, such as a new shirt and a thrifted shirt, so your comparison stays narrow.
2. Map the life-cycle stages you will include, then decide which stages you will leave out and why.
3. Collect emission factors and inventory data from public sources, and record every assumption in one table.
4. Build a baseline calculation for total carbon footprint, then convert it to footprint per wear.
5. Add uncertainty ranges to your main inputs, then run a Monte Carlo simulation to see how often each option wins.
6. Test which variables change the answer most, then turn that result into a simple teen decision tool.

Common Pitfalls

• Mixing data from different system boundaries, which makes one clothing option look better for the wrong reason.
• Treating thrifted clothing as zero-impact, which ignores cleaning, transport, and resale effects.
• Using one flashy emission factor from a blog instead of checking peer-reviewed or government sources.
• Comparing a worn garment to a brand-new garment without matching the number of wears, which distorts the footprint per use.
• Skipping uncertainty analysis, which hides how much the answer depends on your assumptions.

What Makes This Competitive

A strong version of this project does more than compare two totals. It tests how sensitive the answer is to different wear patterns, washing habits, and data sources. You can raise the level by using a clear system boundary, a defensible Monte Carlo model, and a sensitivity test that shows which assumptions matter most. A teen-targeted decision tool also helps, because it turns your analysis into something useful, not just a chart.

Project Variations

• Compare thrifted, fast-fashion, and rental clothing for the same garment type.
• Model the footprint difference between air-drying and machine-drying clothes after repeated wears.
• Compare cotton, polyester, and blended garments using the same life-cycle boundary and uncertainty method.

Learn More

• US EPA Life Cycle Assessment resources: Search the EPA site for LCA basics and system boundary guidance.
• NOAA Climate.gov: Look for background articles on greenhouse gas accounting and climate metrics.
• PubMed: Search for review articles on textile life-cycle assessment and clothing-related emissions.
• Journal of Cleaner Production: Search the journal for peer-reviewed textile LCA studies and reviews.
• MIT OpenCourseWare: Find environmental engineering and sustainability courses that cover LCA methods and uncertainty.
• USDA Economic Research Service: Search for consumer behavior and apparel-related spending data that can support your assumptions.